CN116484413A - Unstructured data-oriented efficient cross-cloud intelligent security layout construction method - Google Patents
Unstructured data-oriented efficient cross-cloud intelligent security layout construction method Download PDFInfo
- Publication number
- CN116484413A CN116484413A CN202310744502.4A CN202310744502A CN116484413A CN 116484413 A CN116484413 A CN 116484413A CN 202310744502 A CN202310744502 A CN 202310744502A CN 116484413 A CN116484413 A CN 116484413A
- Authority
- CN
- China
- Prior art keywords
- data
- cloud
- cloud server
- storage
- algorithm
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000010276 construction Methods 0.000 title claims abstract description 10
- 238000013500 data storage Methods 0.000 claims abstract description 34
- 238000000034 method Methods 0.000 claims abstract description 19
- 230000005540 biological transmission Effects 0.000 claims abstract description 12
- 238000013135 deep learning Methods 0.000 claims abstract description 4
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000013136 deep learning model Methods 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- General Health & Medical Sciences (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Bioethics (AREA)
- Databases & Information Systems (AREA)
- Storage Device Security (AREA)
Abstract
The invention relates to an unstructured data-oriented high-efficiency cross-cloud intelligent security layout construction method which supports intelligent security layout construction of unstructured data crossing multiple public clouds, namely, data scattering, encryption storage and reconstruction are realized. Because the user usually uses public clouds provided by a plurality of cloud service providers when storing data, the risk of information theft by hackers exists in the cloud backup storage process of the data, and the risk of leakage of the user data by a system administrator, a network administrator, a cloud service provider and the like exists after the storage is completed. According to the method, network transmission rate and data storage rate of each cloud are predicted through deep learning, a data storage strategy is intelligently generated by combining CPU utilization rate and memory utilization rate of cloud servers, data is encrypted according to the data storage strategy and then is stored in different cloud servers in a hash mode, and safety and privacy of user data can be guaranteed through the cross-cloud data storage method.
Description
Technical Field
The invention relates to the field of unstructured data hash storage, in particular to a method for constructing an efficient cross-cloud intelligent security layout for unstructured data.
Background
The method for constructing the high-efficiency cross-cloud intelligent security layout for unstructured data is a method for storing data. After data is encrypted and scattered by a certain method, the scattered data blocks are stored into public clouds provided by cloud service providers such as an Arian cloud and a Tencent cloud respectively, and cross-cloud storage of the data is achieved. Compared with the traditional data storage mode, the high-efficiency cross-cloud intelligent safety layout construction method for the data can effectively enhance the safety and privacy of the data, and meanwhile the data storage rate can be accelerated by generating a storage strategy through a deep learning model.
Because unstructured data is easy to be stored by hackers and other personnel to obtain complete user information through illegal means, the method has great threat to the information security of users. However, in the storage process, after the data is encrypted, the data is hashed according to a hash algorithm and stored in different cloud servers, and the cloud servers store the hashed data stored in the cloud servers in different databases after hashing again. And part of hashed user data is stored in each cloud server, so that cloud service providers of different public clouds can only acquire incomplete user information, the user information is effectively prevented from being revealed by the cloud service providers, and the privacy of the user information is improved. When information is intercepted by a hacker in the transmission process, the intercepted information is data hashed by a hash algorithm, so that effective user information cannot be obtained from the intercepted information, and the security of the data is improved. And a storage strategy is automatically generated according to the network transmission rate and the data storage rate of the cloud server through the deep learning model, so that the high efficiency of data storage is improved.
Disclosure of Invention
The technical problem to be solved by the invention is to provide the high-efficiency cross-cloud intelligent safety layout construction method for unstructured data, wherein the encrypted data are scattered into a certain number of data blocks through a hash algorithm, and then the data blocks are stored in different cloud servers according to a storage algorithm, so that the safety of the data can be effectively ensured.
An unstructured data-oriented efficient cross-cloud intelligent security layout construction method, which comprises the following steps: acquiring user uploading data, intelligently observing the change of the data through an upper layer application, if the data does not change within a designated time, automatically capturing the data and reading a data stream; an RSA asymmetric encryption algorithm, wherein a data sender encrypts a data stream by using a public key according to a set specific public key and a private key, and a data receiver decrypts the data according to the private key so as to obtain accurate data; the hash algorithm reads cloud load and analyzes cloud load conditions, predicts data transmission rate and data storage rate of cloud servers through deep learning, acquires the number of currently available cloud servers by combining current work load conditions of the cloud servers, breaks up encrypted data streams through the hash algorithm according to the number of the available cloud servers, and gives specific indexes to each section of broken data; the data storage algorithm is used for carrying out scattered storage on the scattered data, and storing the scattered data into different clouds according to different indexes given to each data segment; and a data reconstruction algorithm, wherein an index algorithm is used for judging cloud of data storage according to the load condition of the cloud server when the data are scattered, and then the data are taken out for reconstruction.
The operation steps of the user uploading data acquisition module comprise:
(1) Detecting the change state of the file uploaded by the user in real time and feeding back to the upper layer application;
(2) The upper layer application judges whether the uploading of the user file is finished or not and whether the data reading can be started or not according to the received file change information;
(3) The file content is read in the form of a data stream.
The RSA asymmetric encryption algorithm comprises the following operation steps:
(1) A pair of prime numbers p and q greater than 1024 bits is selected.
(2) Public key parameters are calculated. Calculating a modulus n=pq, i.e. taking the product of p and q as a modulus value, while finding a public key exponent e, e and f (n) = (p-1)(q-1) mutual mass.
(3) A private key exponent is calculated. The private key exponent d satisfies (de) mod f (n) =1, and the obtained d is the private key exponent.
(4) The public key is (e, n), and the private key is (d, n). When encrypting, firstly, the plaintext is changed into an integer M of 0- (n-1), and then the encryption process is ciphertext C=M≡mod n.
The operation steps of the hash algorithm module comprise:
(1) Network transmission rate V of acquisition cloud server t And the cloud server stores the data to a database D under the cloud server i Data storage rate V of (2) si And inputting the acquired result into a deep learning model. The total data storage rate of the cloud server is noted as V s The calculation formula of the Vs with m servers in total under the cloud server and numbered 1-m is as follows:
；
when the data with the size of 1MB is stored in the cloud server, the time cost of data transmission in the network and the time cost of data storage in the database are set as T, and the calculation formula of T is as follows:
；
taking the data T as a model output result, and sequencing the prediction results T of all cloud servers from small to large;
(2) Screening cloud servers with data T ranking of top 70% for data storage;
(3) Reading the workload of the screened cloud server, and automatically analyzing the workload condition of the cloud server;
(4) Analyzing the workload of the cloud server, wherein n databases under the cloud server are divided into Di (1<=i<=n), the workload utilization of the cloud server is noted asThe CPU utilization rate of the cloud server is marked as P, and the memory utilization rate of the database Di is marked as Mi. Workload utilization of cloud server +.>The calculation formula of (2) is as follows:
；
acquiring the number of cloud servers with workload utilization rate less than ninety percent, namely the number of cloud servers which can be used in the storage;
(5) And (3) according to the number of the available cloud servers obtained in the step (4), the number of the data hash scattering is the number of the available cloud servers, and the unstructured data is scattered by using the hash scattering.
The operation steps of the stored data algorithm comprise:
(1) Sorting the obtained scattered data blocks according to the data size;
(2) Distributing smaller hashed data to a cloud server with a larger T;
(3) Acquiring the number of databases with the memory utilization rate smaller than 90% under the cloud server, and scattering the data hash again according to the acquired number of the databases;
(4) Smaller data blocks are stored into a database with a smaller storage rate according to the data storage rate of the database.
The operation steps of the reconstruction data algorithm module comprise:
(1) Taking the data out of the database according to the index stored in the database and reconstructing according to the hash scattering rule;
(2) According to the encryption unstructured data scattering index, the hashed data are taken out from the cloud server, and the data are recombined to obtain the encryption unstructured data;
(3) And decrypting the data according to the RSA asymmetric encryption algorithm private key to obtain an original unstructured data stream.
The cross-cloud hash encryption storage method of unstructured data based on the technology has good security for data storage. Compared with ordinary hash storage, the method stores the scattered data into different cloud servers, focuses on the workload condition of the cloud servers, and can dynamically judge the number of data blocks to be scattered according to the workload condition of the cloud servers, so that the method is not influenced by too high utilization rate of the workload of the cloud servers, is convenient to use, has high data security and is convenient to store and inquire.
Drawings
FIG. 1 is a flow framework of the present invention;
FIG. 2 is a flow chart of obtaining user upload data in the present invention;
FIG. 3 is a flowchart of an RSA asymmetric encryption algorithm of the present invention;
FIG. 4 is a flow chart of a hashing algorithm of the present invention;
FIG. 5 is a flowchart of a data storage algorithm according to the present invention;
FIG. 6 is a flow chart of the reconstruction data algorithm of the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples. It is to be understood that these examples are illustrative of the present invention and are not intended to limit the scope of the present invention. Further, it is understood that various changes and modifications may be made by those skilled in the art after reading the teachings of the present invention, and such equivalents are intended to fall within the scope of the claims appended hereto.
The invention relates to an unstructured data-oriented high-efficiency cross-cloud intelligent security layout construction method, which comprises the following steps: acquiring user uploading data, intelligently observing the change of the data through an upper layer application, if the data does not change within a designated time, automatically capturing the data and reading a data stream; an RSA asymmetric encryption algorithm, wherein a data sender encrypts a data stream by using a public key according to a set specific public key and a private key, and a data receiver decrypts the data according to the private key so as to obtain accurate data; the hash algorithm reads cloud load and analyzes cloud load conditions, predicts data transmission rate and data storage rate of cloud servers through deep learning, acquires the number of currently available cloud servers by combining current work load conditions of the cloud servers, breaks up encrypted data streams through the hash algorithm according to the number of the available cloud servers, and gives specific indexes to each section of broken data; the data storage algorithm is used for carrying out scattered storage on the scattered data, and storing the scattered data into different clouds according to different indexes given to each data segment; and a data reconstruction algorithm, wherein an index algorithm is used for judging cloud of data storage according to the load condition of the cloud server when the data are scattered, and then the data are taken out for reconstruction.
In connection with the first figure, the overall flow framework of the present invention.
In combination with the second drawing, the operation steps of the user uploading data obtaining module include:
(1) Detecting the change state of the file uploaded by the user in real time and feeding back to the upper layer application;
(2) The upper layer application judges whether the uploading of the user file is finished or not and whether the data reading can be started or not according to the received file change information;
(3) The file content is read in the form of a data stream.
In combination with the third diagram, the RSA asymmetric encryption algorithm comprises the following operation steps:
(1) A prime number p and q having a pair number of bits greater than 1024 bits is selected.
(2) Public key parameters are calculated. Calculating a modulus n=pq, i.e. taking the product of p and q as a modulus value, while finding a public key exponent e, e and f (n) = (p-1)（q-1）Mutually good quality.
(3) A private key exponent is calculated. The private key exponent d satisfies (de) mod f (n) =1, and the obtained d is the private key exponent.
(4) The public key is (e, n), and the private key is (d, n). When encrypting, firstly, the plaintext is changed into an integer M of 0- (n-1), and then the encryption process is ciphertext C=M≡mod n.
With reference to fig. four, the operation steps of the hash algorithm module include:
(1) Network transmission rate V of acquisition cloud server t And the cloud server stores the data to a database D under the cloud server i Data storage rate V of (2) si And inputting the acquired result into a deep learning model. The total data storage rate of the cloud server is noted as V s The calculation formula of the Vs with m servers in total under the cloud server and numbered 1-m is as follows:
；
when the data with the size of 1MB is stored in the cloud server, the time cost of data transmission in the network and the time cost of data storage in the database are set as T, and the calculation formula of T is as follows:
；
taking the data T as a model output result, and sequencing the prediction results T of all cloud servers from small to large;
(2) Screening cloud servers with data T ranking of top 70% for data storage;
(3) Reading the workload of the screened cloud server, and automatically analyzing the workload condition of the cloud server;
(4) Analyzing the workload of the cloud server, wherein n databases under the cloud server are divided into Di (1<=i<=n), the workload utilization of the cloud server is noted asThe CPU utilization rate of the cloud server is marked as P, and the memory utilization rate of the database Di is marked as Mi. Workload utilization of cloud server +.>The calculation formula of (2) is as follows:
；
acquiring the number of cloud servers with workload utilization rate less than ninety percent, namely the number of cloud servers which can be used in the storage;
(5) And (3) according to the number of the available cloud servers obtained in the step (4), the number of the data hash scattering is the number of the available cloud servers, and the unstructured data is scattered by using the hash scattering.
With reference to fig. five, the operation steps of the stored data algorithm include:
(1) Sorting the obtained scattered data blocks according to the data size;
(2) Distributing smaller hashed data to a cloud server with a larger T;
(3) Acquiring the number of databases with the memory utilization rate smaller than 90% under the cloud server, and scattering the data hash again according to the acquired number of the databases;
(4) Smaller data blocks are stored into a database with a smaller storage rate according to the data storage rate of the database.
In combination with the sixth diagram, the operation steps of the reconstruction data algorithm module include:
(1) Taking the data out of the database according to the index stored in the database and reconstructing according to the hash scattering rule;
(2) According to the encryption unstructured data scattering index, the hashed data are taken out from the cloud server, and the data are recombined to obtain the encryption unstructured data;
(3) And decrypting the data according to the RSA asymmetric encryption algorithm private key to obtain an original unstructured data stream.
Claims (6)
1. The method for constructing the high-efficiency cross-cloud intelligent security layout for unstructured data is characterized by comprising the following steps of: acquiring user uploading data, intelligently observing the change of the data through an upper layer application, if the data does not change within a designated time, automatically capturing the data and reading a data stream; an RSA asymmetric encryption algorithm, wherein a data sender encrypts a data stream by using a public key according to a set specific public key and a private key, and a data receiver decrypts the data according to the private key so as to obtain accurate data; the hash algorithm reads cloud load and analyzes cloud load conditions, predicts data transmission rate and data storage rate of cloud servers through deep learning, acquires the number of currently available cloud servers by combining current work load conditions of the cloud servers, breaks up encrypted data streams through the hash algorithm according to the number of the available cloud servers, and gives specific indexes to each section of broken data; the data storage algorithm is used for carrying out scattered storage on the scattered data, and storing the scattered data into different clouds according to different indexes given to each data segment; and a data reconstruction algorithm, wherein an index algorithm is used for judging cloud of data storage according to the load condition of the cloud server when the data are scattered, and then the data are taken out for reconstruction.
2. The method for constructing an unstructured data-oriented efficient cross-cloud intelligent security layout according to claim 1, wherein the obtaining a user uploading data module comprises: (1) Automatically detecting the change state of the file uploaded by the user in real time and feeding back to the upper layer application; (2) The upper layer application judges whether the uploading of the user file is finished or not and whether the data reading can be started or not according to the received file change information; (3) reading the file content in the form of a data stream.
3. The method for constructing an unstructured data-oriented efficient cross-cloud intelligent security layout according to claim 1, wherein the RSA asymmetric encryption algorithm comprises: (1) Selecting a pair ofPrime numbers p and q with more than 1024 bits; (2) Calculating public key parameters, calculating a modulus n=pq, i.e. taking the product of p and q as a modulus value, while finding a public key exponent e, e and f (n) = (p-1)(q-1) intersubstance; (3) Calculating a private key exponent, the private key exponent d satisfying (de) mod f (n) =1, and the obtained d is the private key exponent; (4) The public key is (e, n), the private key is (d, n), and when encrypting, the plaintext is changed into an integer M of 0- (n-1), and then the encrypting process is ciphertext C=M≡mod n.
4. The unstructured data-oriented efficient cross-cloud intelligent security layout construction method of claim 1, wherein the hashing algorithm comprises: (1) Network transmission rate V of acquisition cloud server t The cloud server stores the data to a database D under the cloud server i Data storage rate V of (2) si Inputting the acquired results into a deep learning model, and recording the total data storage rate of the cloud server as V s The calculation formula of the Vs with m servers in total under the cloud server and numbered 1-m is as follows:
；
when the data with the size of 1MB is stored in the cloud server, the time cost of data transmission in the network and the time cost of data storage in the database are set as T, and the calculation formula of T is as follows:
；
data T is taken as a model output result, andthe prediction results T of all cloud servers are sequenced from small to large; (2) Screening cloud servers with data T ranking of top 70% for data storage; (3) Reading the workload of the screened cloud server, and automatically analyzing the workload condition of the cloud server; (4) Analyzing the workload of the cloud server, wherein n databases under the cloud server are divided into D i （1<=i<=n), the workload utilization of the cloud server is noted asThe CPU utilization rate of the cloud server is recorded as P, and the database D i The memory utilization of (2) is recorded as M i Workload utilization of cloud server +.>The calculation formula of (2) is as follows:
；
acquiring the number of cloud servers with workload utilization rate less than ninety percent, namely the number of cloud servers which can be used in the storage; (5) And (3) dynamically changing the number of data hashes according to the number of available cloud servers obtained in the step (4), and scattering unstructured data by using hash scattering.
5. The unstructured data-oriented efficient cross-cloud intelligent security layout construction method of claim 4, wherein the stored data algorithm further comprises: (1) Sorting the obtained scattered data blocks according to the data size; (2) Distributing smaller hashed data to a cloud server with a larger T; (3) Acquiring the number of databases with the memory utilization rate smaller than 90% under the cloud server, and scattering the data hash again according to the acquired number of the databases; (4) Smaller data blocks are stored into a database with a smaller storage rate according to the data storage rate of the database.
6. The method for constructing the unstructured data-oriented efficient cross-cloud intelligent security layout according to claim 1, wherein the data reconstruction algorithm comprises the following steps: (1) Taking the data out of the database according to the index stored in the database and reconstructing according to the hash scattering rule; (2) According to the encryption unstructured data scattering index, the hashed data are taken out from the cloud server, and the data are recombined to obtain the encryption unstructured data; (3) And decrypting the data according to the RSA asymmetric encryption algorithm private key to obtain an original unstructured data stream.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310744502.4A CN116484413B (en) | 2023-06-25 | 2023-06-25 | Unstructured data-oriented efficient cross-cloud intelligent security layout construction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310744502.4A CN116484413B (en) | 2023-06-25 | 2023-06-25 | Unstructured data-oriented efficient cross-cloud intelligent security layout construction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116484413A true CN116484413A (en) | 2023-07-25 |
| CN116484413B CN116484413B (en) | 2023-09-29 |
Family
ID=87212331
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310744502.4A Active CN116484413B (en) | 2023-06-25 | 2023-06-25 | Unstructured data-oriented efficient cross-cloud intelligent security layout construction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116484413B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150356171A1 (en) * | 2014-06-05 | 2015-12-10 | Harmon.Ie R&D Ltd. | System and method for cross-cloud topic matching |
| US20170085372A1 (en) * | 2015-09-17 | 2017-03-23 | Secturion Systems, Inc. | Client(s) to cloud or remote server secure data or file object encryption gateway |
| CN107040412A (en) * | 2017-03-31 | 2017-08-11 | 南京邮电大学 | A kind of Cloud Server load predicting method |
| CN109583221A (en) * | 2018-12-07 | 2019-04-05 | 中国科学院深圳先进技术研究院 | Dropbox system based on cloudy server architecture |
| CN109739433A (en) * | 2018-11-27 | 2019-05-10 | 中科恒运股份有限公司 | The method and terminal device of data processing |
| US20210096753A1 (en) * | 2019-09-26 | 2021-04-01 | National Taiwan University | Cloud secured storage system |
| CN113596094A (en) * | 2021-06-29 | 2021-11-02 | 付腾瑶 | Load balancing method and device based on cloud cluster |
| US20210385247A1 (en) * | 2020-06-05 | 2021-12-09 | Queen's University At Kingston | Secure Cloud Communication Architecture |
| CN113886217A (en) * | 2021-08-24 | 2022-01-04 | 阿里云计算有限公司 | Gray level verification method, device and system for cloud database service and storage medium |
| WO2022142112A1 (en) * | 2020-12-31 | 2022-07-07 | 平安科技（深圳）有限公司 | Blockchain-based mail processing method, and mail sending end, mail receiving end and device |
| CN115022044A (en) * | 2022-06-02 | 2022-09-06 | 联通(广东)产业互联网有限公司 | Storage method and system based on multi-cloud architecture |
| CN115544314A (en) * | 2022-10-09 | 2022-12-30 | 武汉众邦银行股份有限公司 | Unstructured database system |
-
2023
- 2023-06-25 CN CN202310744502.4A patent/CN116484413B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150356171A1 (en) * | 2014-06-05 | 2015-12-10 | Harmon.Ie R&D Ltd. | System and method for cross-cloud topic matching |
| US20170085372A1 (en) * | 2015-09-17 | 2017-03-23 | Secturion Systems, Inc. | Client(s) to cloud or remote server secure data or file object encryption gateway |
| CN107040412A (en) * | 2017-03-31 | 2017-08-11 | 南京邮电大学 | A kind of Cloud Server load predicting method |
| CN109739433A (en) * | 2018-11-27 | 2019-05-10 | 中科恒运股份有限公司 | The method and terminal device of data processing |
| CN109583221A (en) * | 2018-12-07 | 2019-04-05 | 中国科学院深圳先进技术研究院 | Dropbox system based on cloudy server architecture |
| US20210096753A1 (en) * | 2019-09-26 | 2021-04-01 | National Taiwan University | Cloud secured storage system |
| US20210385247A1 (en) * | 2020-06-05 | 2021-12-09 | Queen's University At Kingston | Secure Cloud Communication Architecture |
| WO2022142112A1 (en) * | 2020-12-31 | 2022-07-07 | 平安科技（深圳）有限公司 | Blockchain-based mail processing method, and mail sending end, mail receiving end and device |
| CN113596094A (en) * | 2021-06-29 | 2021-11-02 | 付腾瑶 | Load balancing method and device based on cloud cluster |
| CN113886217A (en) * | 2021-08-24 | 2022-01-04 | 阿里云计算有限公司 | Gray level verification method, device and system for cloud database service and storage medium |
| CN115022044A (en) * | 2022-06-02 | 2022-09-06 | 联通(广东)产业互联网有限公司 | Storage method and system based on multi-cloud architecture |
| CN115544314A (en) * | 2022-10-09 | 2022-12-30 | 武汉众邦银行股份有限公司 | Unstructured database system |
Non-Patent Citations (1)
| Title |
|---|
| 胡博 等: "基于混合云架构的国家城市供水全过程监管平台", 《给水排水》, pages 136 - 139 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116484413B (en) | 2023-09-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Lu | A new communication-efficient privacy-preserving range query scheme in fog-enhanced IoT | |
| CN105871543B (en) | Multiple key cipher text retrieval method under more data owner's backgrounds based on attribute | |
| US7856100B2 (en) | Privacy-preserving data aggregation using homomorphic encryption | |
| CN107734021A (en) | block chain data uploading method, system, computer system and storage medium | |
| Yu et al. | Toward data security in edge intelligent IIoT | |
| CN103944711B (en) | Cloud storage ciphertext retrieval method and system | |
| WO2018184407A1 (en) | K-means clustering method and system having privacy protection | |
| CN106921493B (en) | Encryption method and system | |
| CN114244498B (en) | Dynamic searchable public key encryption method with forward security | |
| CN1771487A (en) | Method and apparatus for limiting number of times contents can be accessed using hashing chain | |
| KR20080030344A (en) | Method and apparatus for broadcast encryption using bilinear map | |
| JP6770075B2 (en) | Encrypted message search method, message sending / receiving system, terminal, program | |
| CN114338038B (en) | Storage system for secret inquiry of block chain data and careless transmission method | |
| CN109145079A (en) | Cloud based on personal interest user model can search for encryption method | |
| CN109284426B (en) | Multi-data document classification system based on permission level | |
| Rauthan et al. | Homomorphic encryption approach for exploration of sensitive information retrieval | |
| CN107086917A (en) | The encryption method that a kind of parallelization and structuring public key can search for | |
| CN116484413B (en) | Unstructured data-oriented efficient cross-cloud intelligent security layout construction method | |
| CN108011713A (en) | Cipher text retrieval method based on homomorphic cryptography in a kind of cloud storage | |
| KR101232385B1 (en) | Searchable Symmetric Encryption Method and System | |
| CN108632257B (en) | Method and system for acquiring encrypted health record supporting hierarchical search | |
| KR100951034B1 (en) | Method of producing searchable keyword encryption based on public key for minimizing data size of searchable keyword encryption and method of searching data based on public key through that | |
| Jiang et al. | A novel privacy preserving keyword search scheme over encrypted cloud data | |
| Abdalwahid et al. | A New Efficient Method for Information Security in Hadoop | |
| Zhu et al. | Verification of boolean queries over outsourced encrypted data based on counting bloom filter |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |